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ORCIDAntoine Houdard
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2020 – today
- 2024
[j6]Clément Weinreich, Leonardo de Oliveira, Antoine Houdard, Georges Nader:
Real-Time Neural Materials using Block-Compressed Features. Comput. Graph. Forum 43(2): i-iii (2024)- [c5]Jean Prost, Antoine Houdard, Andrés Almansa
, Nicolas Papadakis:
Efficient Posterior Sampling for Diverse Super-Resolution with Hierarchical VAE Prior. VISIGRAPP (3): VISAPP 2024: 393-400 - 2023
- [j5]Antoine Houdard, Arthur Leclaire, Nicolas Papadakis, Julien Rabin:
A Generative Model for Texture Synthesis based on Optimal Transport Between Feature Distributions. J. Math. Imaging Vis. 65(1): 4-28 (2023) - [j4]Antoine Houdard, Arthur Leclaire, Nicolas Papadakis, Julien Rabin:
On the Gradient Formula for learning Generative Models with Regularized Optimal Transport Costs. Trans. Mach. Learn. Res. 2023 (2023) - [c4]Jean Prost, Antoine Houdard, Andrés Almansa, Nicolas Papadakis:
Inverse problem regularization with hierarchical variational autoencoders. ICCV 2023: 22837-22848 - [i7]Jean Prost, Antoine Houdard, Andrés Almansa, Nicolas Papadakis:
Inverse problem regularization with hierarchical variational autoencoders. CoRR abs/2303.11217 (2023) - [i6]Clément Weinreich, Louis de Oliveira, Antoine Houdard, Georges Nader:
Real-Time Neural Materials using Block-Compressed Features. CoRR abs/2311.16121 (2023) - 2022
- [j3]Johannes Hertrich, Antoine Houdard, Claudia Redenbach:
Wasserstein Patch Prior for Image Superresolution. IEEE Trans. Computational Imaging 8: 693-704 (2022) - [i5]Jean Prost, Antoine Houdard, Nicolas Papadakis, Andrés Almansa:
Diverse super-resolution with pretrained deep hiererarchical VAEs. CoRR abs/2205.10347 (2022) - 2021
- [c3]Antoine Houdard, Arthur Leclaire, Nicolas Papadakis, Julien Rabin:
Wasserstein Generative Models for Patch-Based Texture Synthesis. SSVM 2021: 269-280 - [c2]Jean Prost, Antoine Houdard, Andrés Almansa, Nicolas Papadakis:
Learning Local Regularization for Variational Image Restoration. SSVM 2021: 358-370 - [i4]Antoine Houdard, Arthur Leclaire, Nicolas Papadakis, Julien Rabin:
On the Existence of Optimal Transport Gradient for Learning Generative Models. CoRR abs/2102.05542 (2021) - [i3]Jean Prost, Antoine Houdard, Andrés Almansa, Nicolas Papadakis:
Learning local regularization for variational image restoration. CoRR abs/2102.06155 (2021) - [i2]Johannes Hertrich, Antoine Houdard, Claudia Redenbach:
Wasserstein Patch Prior for Image Superresolution. CoRR abs/2109.12880 (2021) - 2020
- [i1]Antoine Houdard, Arthur Leclaire, Nicolas Papadakis, Julien Rabin:
Wasserstein Generative Models for Patch-based Texture Synthesis. CoRR abs/2007.03408 (2020)
2010 – 2019
- 2019
- [c1]Antoine Houdard:
Statistical Modeling of the Patches DC Component for Low-Frequency Noise Reduction. EUSIPCO 2019: 1-5 - 2018
- [b1]Antoine Houdard:
Some advances in patch-based image denoising. (Quelques avancées dans le débruitage d'image par patchs). Télécom ParisTech, France, 2018 - [j2]Antoine Houdard, Charles Bouveyron, Julie Delon:
High-Dimensional Mixture Models for Unsupervised Image Denoising (HDMI). SIAM J. Imaging Sci. 11(4): 2815-2846 (2018) - 2017
- [j1]Antoine Houdard, Andrés Almansa, Julie Delon:
Demystifying the Asymptotic Behavior of Global Denoising. J. Math. Imaging Vis. 59(3): 456-480 (2017)
Coauthor Index
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